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Centro Europeo di Risonanze Magnetiche

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1 Centro Europeo di Risonanze Magnetiche
una infrastruttura di ricerca nel Polo Scientifico dell’Università di Firenze Claudio Luchinat CERM Università di Firenze

2 Il Polo Scientifico di Sesto Fiorentino

3 The Magnetic Resonance Center in Florence
700b Bio-labs 800 950 850ss 900 700 Conference room Library 400 Workshop 500 Computer room 600 600b 700ss Department of Chemistry (offices, bio-labs, relaxometer, instruments..) GENEXPRESS, CRYST, CISM DaVEB Biobank

4 CERM instrumentation NMR instrumentation 700 MHz WB Cryo 900 MHz
700 MHz (a) Cryo 700 MHz (b) Cryo 800 MHz 400 MHz 600 MHz Cryo 900 MHz 850 MHz WB Cryo 950 MHz

5 The Magnetic Resonance Center in Florence
Protein structure determination Methodological advancements in NMR Solid state NMR ICT and computational biology Electron/nuclear relaxation (Relaxometry) Drug discovery Structural proteomics Metabolomics 700b Bio-labs 800 950 850ss 900 700 Conference room Library 400 Workshop 500 Computer room 600 600b 700ss We provide access to European researchers since 1994 New access program Bio-NMR ( ) started September 2010 Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble, Berlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, Goteborg Department of Chemistry (offices, bio-labs, relaxometer, instruments..) GENEXPRESS, CRYST, CISM DaVEB Biobank

6 uno sguardo molecolare sulla salute e sulle malattie
Metabolomica: uno sguardo molecolare sulla salute e sulle malattie Claudio Luchinat CERM Università di Firenze

7 The Research Centers of FiorGen
CERM Scientific Campus Sesto Fiorentino Biomedical Campus Careggi

8 Scientific Publications
146 publications on high level journals, starting from 2004 Independent reviewers attested the high scientific level of the Foundation “The scientific production of FiorGen is quite impressive” Prof. Arturo Falaschi Scuola Normale Superiore – Pisa Distinguished Scientist ICGEB Trieste Aprile 2008 “The scientific productivity of FiorGen is of excellent level” Prof. Giuseppe Novelli Tor Vergata University of Rome University of Arkansas (USA) WPQ PGx EMEA (UK) Maggio 2008

9 What is Metabolomics? Metabolomics is a further “omic” science that is now emerging with the purpose of “elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites in an organism or cell”. Genomics tells you what could happen. Metabolomics tells you what has happened. Only a few thousand metabolites. !! However, not negligible external variability !! (source of noise) 9 9

10 Examples of metabolites
H P y r u v i c a d S n x l o e t Acetyl CoA

11 + Metabolomics Study of small molecules in biological fluids
Metabolic fingerprint

12 1H NMR spectrum of ethanol
__ |

13 1H NMR spectrum (upfield part) of human urine

14 1H NMR spectrum (downfield part) of human urine

15 2 Routes to Metabolomics (fingerprinting and pattern recognition)
Two approaches: Identify as many metabolites as possible Use the whole spectrum as a fingerprint (statistics) 1 2 3 4 5 6 7 ppm Quantitative methods Chemometric methods (fingerprinting and pattern recognition) -25 -20 -15 -10 -5 5 10 15 20 25 -30 PC1 PC2 1 2 3 4 5 6 7 ppm hippurate urea allantoin creatinine 2-oxoglutarate citrate TMAO succinate fumarate water taurine

16 The fingerprint Metabolomics: Traditional clinical analysis:
Few already known metabolites for some disease (e.g. glucose for diabetes, etc…) All metabolites are analyzed together without prior knowledge 16

17 The fingerprint What are they doing ? 17

18 The fingerprint Only an analysis at a global level can tell the whole story 18

19 METabolomic REFerence
Ind 1 Ind 2 19 19

20 METabolomic REFerence
Ind 1 Ind 2 20 20

21 METabolomic REFerence
Convex hulls of 22 donors in the three most significant PCA-CA dimensions PCA for data reduction CA for obtain well separated clusters KNN for classification 99% accuracy in montecarlo cross validation “natural” gender discrimination MALE FEMALE Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008, 105,

22 The signature of Our Body
There exists an individual human metabolic phenotype (metabotype) The metabotype consists of a variable part (environment) and an invariant part (genetics + environment) The invariant part persists for at least two-three years (if the diet is averaged using collection of multiple samples) The discovery of the existence of individual metabotypes is the baseline for Biomedical Researches Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008 Bernini, P.; Bertini, I.; Luchinat, C.; Nepi, S.; Saccenti, E.; Schäfer, H.; Schütz, B.; Spraul, M.; Tenori, L. J. Prot. Res. 2009

23 Metabolomics @CERM/CIRMMP
Collaborative Projects SPIDIA (7th framework program) Standardization and improvement of pre-analytical procedures for in-vitro diagnostics. CHANCE (7th framework program) Evaluation of the impact of nutritional criticalities in population at risk of poverty using NMR metabolomics. livSYSiPS (ErasysBio+) The sistem biology of network stress based on data generated from in vitro differentiated hepatocytes derived from individual-specific human iPS cells. ITFoM (FET Flagship Initiative) The aim of ITFoM is to develop models of human pathways, tissues, and ultimately of the whole human, to create a “virtual patient” which will enable physicians to identify personalised prevention schedules and treatments adapted to each person. Progetto COSMOS (EU Coordination action) To develop new standard for metabolomics sutdies Progetto BioMedBridges (EU Coordination action) To develop a unified framework for biomedical studies in Europe Progetto Melanoma (Ente Cassa di Risparmio di Firenze) New strategies for diagnosis prognosis and treatment of melanoma.

24 Metabolomics @CERM/CIRMMP
Collaborations Celiac Disease (Prof. Antonio Calabrò, Careggi Hospital) Geriatric patients (Dr. Laura Biganzoli, Prato Hospital) Diabetes in young (Dr. Sonia Toni, Mayer Children’s Hospital) BPCO (Dr. Massimo Miniati, Careggi Hospital and CNR Pisa) Metastatic Colorectal Cancer (Dr. Benny W. Jensen, Herlev Hospital, Copenhagen) Periodonitis (Dr. Mario Aimetti, University of Turin) Bladder and Prostate Cancer (Dr. Marco Carini, Careggi Hospital) Cardiovascular Risk (Dr. Adriana Tognaccini, Pistoia Hospital and AVIS Toscana) Intestinal Bowel Diseases (Prof. Maurizio Vecchi, University of Milan) Heart Failure (Prof. Franco Gensini, University of Florence) Breast Cancer (Dr. Angelo Di Leo, Prato Hospital) Bariatric Surgery (Prof. Bernd Schultes, St. Gallen Hospital, Switzerland) Metabolomics of the Mitochondrion (Prof. Roland Lill, University of Marburg, Germany) Osteoarthritis (Prof. Brandi, University of Florence) Krabbe disease (Dott.sa Alice Luddi, University of Siena) Gestational diabetes (Dr. Dani, Careggi Hospital)

25 Celiac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectra Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

26 Celiac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectra and corresponding Follow-up Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

27 There exist a metabolic fingerprint of celiac disease
Celiac – Healthy Subjects – Cross: predicted Potential Celiac These alteration are present also in potential celiac subjects: so they precede the intestinal damage Potential CD largely shares the metabonomic signature of overt CD. Most metabolites found to be significantly different between control and CD subjects were also altered in potential CD. Our results suggest early institution of GFD in patients with potential CD Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170 Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J. Proteome Res. 2010

28 http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org

29 Breast cancer metabolomics
Classification between Pre-Op and Metastatic subjects. Accuracy ~80% Other comparisons NOESY CPMG Healthy vs Met Accuracy Healthy vs Met Accuracy 72.67% 73.44% Healthy vs Post-op Accuracy 70.00% Healthy vs Post-op Accuracy 75.80% Post vs Met Accuracy 74.96% Post-op vs Met Accuracy 70.00% 29

30 Colorectal Cancer Metabolomics
Serum samples from 139 HS and 155 patients with mCRC, included in a prospective phase II study of 3rd line treatment with cetuximab and irinotecan We can discriminate healthy controls from mCRC with almost 100% accuracy. We can predict the overall survival of the patients Cross-validated results on the Training Set: Sensitivity : 79.9% Specificity: 76.4% Accuracy: 78.5% Univariate Cox Regression Analysis for the Validation Set: HR: 3.30 95% CI: to 5.37 P: ∙ 10-6 PLS-CA model: long survival, in blue; short survival, in yellow Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P., Cancer Res Jan 1;72(1): Epub 2011 Nov 11 30 30 30 30

31 Heart failure metabolomics
Classification between different subgroups of Heart failure patients (1D CPMG spectra). Sensitivity Specificity Accuracy CMD vs CMS 45.52% 68.29% 61.19% NYHA1 vs NYHA 2 61.88% 71.42% 67.71% NYHA2 vs NYHA 3/4 73.62% 56.44% 68.04% NYHA 1 vs NYHA 3/4 74.83% 68.55% 72.15% Patients vs Healthy 85.11% 91.04% 87.29% Patients are separated from healthy, but there is not any significant difference between the disease grading that could reflect the clinical severity of the disease. Although good discrimination between healthy and HF subjects with a severe disease, if not expected, was easy to be hypothesized, a comparable good discrimination ability between healthy and HF subjects with a mild disease was unexpected and appears rather counter-intuitive. 31 31 31 31

32 Metabolomics of Melanoma
NOESY Spectra SERUM URINE Sensitivity (%) Specificity (%) Accuracy (%) Healthy vs. Melanoma 91.38 81.67 89.89 95.46 70.52 91.37 Stage I/II vs. Healthy 85.49 85.34 85.25 91.03 79.02 87.46 Stage III/IV vs. Healthy 88.84 91.40 89.3 85.44 80.25 82.93 Stage I/II vs III/IV 85.18 73.28 79.94 75.40 67.86 72.98 32 32

33 Fingerprint of Obesity
NW vs SO 94.0 OW vs SO 79.6 NW vs OW 69.7 NW vs OW+SO 87.8 NW+OW vs SO 84.1 The prediction of OW (stars) using the NW (green) vs SO (blue) model classify almost all OW as SO (except two) 33 33

34 Da Vinci European BioBank

35 http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Metabolomica L’approccio combinato di metabolomica (Prof. Claudio Luchinat) e biobanca (Prof. Paola Turano) ci rende unici in questo settore della scienza FROM METABOLOMICS Metabolomic analysis Validation of sample quality in biobanks Definition of new SOPs TO BIOBANKS Dalla Metabolomica Analisi Metabolomica Controllo Qualità di campioni Nelle biobanche Definizione di Nuove SOP Alle Biobanche Spettro NMR di urina di un donatore sano https://www. davincieuropeanbiobank.org

36 http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Fiorgen ha implementato una Biobanca su standard europei che è inserita nei programmi nazionali ed europei. Essa raccoglie campioni biologici (sangue, urine, biopsie) di molte malattie . Collezioni di campioni della Biobanca: Scompenso cardiaco (Prof. Gianfranco Gensini) Melanoma (Prof. Nicola Pimpinelli) Cancro alla mammella (Prof. Angelo Di Leo, e USA) Cancro al colon (Prof. Benny V. Jensen, Danimarca) Disturbi alla prostata (Prof. Marco Carini) Celiachia (Prof. Antonio Calabrò) Osteoporosi (Prof.ssa Maria Luisa Brandi) https://www. davincieuropeanbiobank.org

37 The Future of Medicine Metabolomics can monitor the same individual in a multidimensional space hepatocarcinoma Colorectal cancer cirrhosis steatosis Intestinal bowel disease Metabolic syndrome Healthy aging Diabetes Hypertension Hearth Failure 37

38 Et interviene di questa come dicono e’ fisici dello etico, che nel principio del suo male è facile a curare e difficile a conoscere, ma, nel progresso del tempo, non l’avendo in principio conosciuta né medicata, diventa facile a conoscere e difficile a curare. Machiavelli, Il Principe, cap. 3

39 http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Il sogno Dotare ogni cittadino di un chip in cui sono riportati il genoma, il proteoma e il metaboloma al fine di monitorarne nel tempo lo stato di salute https://www. davincieuropeanbiobank.org

40 From general to personalized medicine
The Future of Medicine From general to personalized medicine 40

41 Ivano Bertini December 6, 1940 – July 7, 2012

42

43

44 Metabolomics @CERM/CIRMMP Metabolomics Publications
Human phenotypes Assfalg M, Bertini I, Colangiuli D, Luchinat C, Schäfer H, Schütz B, Spraul M. Evidence of different metabolic phenotypes in humans. Proc Natl Acad Sci U S A 2008;105(5): (IF=9.771). Bernini P, Bertini I, Luchinat C, Nepi S, Saccenti E, Schäfer H, Schütz B, Spraul M, Tenori L. Individual human phenotypes in metabolic space and time. J Proteome Res Sep;8(9): (IF=5.460). Cardiovascular diseases Bernini P, Bertini I, Luchinat C, Tenori L, Tognaccini A. The cardiovascular risk of healthy individuals studied by NMR metabonomics of plasma samples. J Proteome Res [Epub ahead of print] (IF=5.460). Celiac disease Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J Proteome Res 2011 Feb 4;10(2): (IF=5.460). Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, Renzi D, Saccenti E, Tenori L. The metabonomic signature of celiac disease. J Proteome Res Jan;8(1): (IF=5.460). Ozono terapy Travagli V, Zanardi I, Bernini P, Nepi S, Tenori L, Bocci V. Effects of ozone blood treatment on the metabolite profile of human blood. Int J Toxicol 2010;29(2): (IF=1.762).

45 Metabolomics @CERM/CIRMMP
Breast cancer Tenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, Biganzoli L, Arbushites MC, Luchinat C, Bertini I, Di Leo A. Exploration of serum metabolomic profiles and outcomes in women with metastatic breast cancer: A pilot study. Mol Oncol Jun 1. (IF=4.250). Oakman C, Tenori L, Claudino WM, Cappadona S, Nepi S, Battaglia A, Bernini P, Zafarana E, Saccenti E, Fornier M, Morris PG, Biganzoli L, Luchinat C, Bertini I, Di Leo A. Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods. Ann Oncol 2011 Jun;22(6): (IF=6.452). Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A. Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol 2011 Jul;43(7): Review. (IF=4.956). Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A. Metabolomics: available results, current research projects in breast cancer, and future applications. J Clin Oncol Jul 1;25(19): (IF=18.970). Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L. New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol. 2007;18 Suppl 12:xii8-14. Review. (IF=6.452). Colorectal Cancer Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Res Jan 1;72(1): (IF=8.234).

46 Metabolomics @CERM/CIRMMP
Peridontal diseases Mario Aimetti, Stefano Cacciatore, Antonio Graziano and Leonardo Tenori. Metabonomic analysis of saliva reveals generalized chronic periodontitis signature. Metabolomics; Online First™ (IF=3.608). Standard Operating Procedures Bernini P, Bertini I, Luchinat C, Nincheri P, Staderini S, Turano P. Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR Apr;49(3-4): (IF=3.047). The future of medicine Bertini I; Luchinat C; Tenori L. Metabolomics for the future of personalized medicine through information and communication technologies. PERSONALIZED MEDICINE Volume: 9 Issue: 2 (IF=0.783).

47 Our interest in metabolomics
Metabolic signature of individuals: Metabolic phenotype Metabolic signature of diseases Coeliac disease tumor  metastasis heart failure, pulmonary diseases,etc… Metabolites and biobank samples Sensitive reporters of stability Assess sample preparation and preanalytical procedures SOP

48 Metabolomics steps Handling and preparation of samples NMR analysis
Metabolites identification Statistical analysis Data processing and bucketing 48 48 48

49 BioBank Project Collect Store Processing Distribute
Biological samples for scientific research

50 The need for individual metabolomic screening
The Future of Medicine The need for individual metabolomic screening We are proposing to collect individual metabolomics data for a large screening of the Tuscany population 50

51 The FiorGen Foundation

52 How was FiorGen born FiorGen Foundation, a “non-profit organization of social utility” (ONLUS), was founded in 2002, with the purpose of favoring scientific, cultural and social development. FiorGen Foundation is the result of a strong link between different scientific actors such as the Magnetic Resonance Center (CERM) of the Scientific Campus of Sesto Fiorentino and the Biomedical Campus of Careggi, which has been supported by the Chamber of Commerce, Industry and Handicrafts of Florence and the Ente Cassa di Risparmio of Florence.

53 ADMINISTRATION COUNCIL
Governing Bodies ADMINISTRATION COUNCIL Vasco Galgani (President) Calogero Surrenti (Vicepresident) Gianni Amunni Paolo Asso Lucia Banci Francesco Barbolla Ivano Bertini Gianfranco Gensini Claudio Luchinat SCIENTIFIC COMMITTEE Ivano Bertini (President) Rosanna Abbate Andrea Galli Maurizio Genuardi Cristina Nativi

54 Fund Raising CF: 94100210486 Campaign "Adopt a Researcher"
Charity auction “Art and Solidarity for the research” CF:

55 Communication Newsletter FiorGenews n n n n.4

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61 Research Areas of FiorGen
Research Area 1: Bersagli e farmaci antitumorali Agonisti di recettori nucleari nella modulazione della crescita ed invasività tumorale Delezione organo specifica del recettore ARP-1 in modelli murini Research Area 2: Fisiopatologia e farmacogenetica delle malattie cardiovascolari Progetto Malattia Aneurismatica e Carotidea Progetto variabilità nella risposta alla terapia antiaggregante (aspirina e clopidogrel) Research Area 3: Origine malattie genetiche Studio delle basi genetiche della predisposizione a neoplasie umane Studi sull'origine della Sclerosi Laterale Amiotrofica Caratterizzazione strutturale della proteina beta amiloide coinvolta nel morbo di Alzheimer Research Area 4: Metabolomica Research Area 5: BioBanca da Vinci European BioBank - daVEB Research Area 6: Melanoma: nuovi possibili biomarcatori di diagnosi e progressione


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